no code implementations • 13 May 2022 • Mahdieh Kazemimoghadam, Zi Yang, Lin Ma, Mingli Chen, Weiguo Lu, Xuejun Gu
We proposed to leverage the consistency of organs' anatomical shape and position information in medical images.
no code implementations • 19 Apr 2021 • Mingli Chen, Andreas Joseph, Michael Kumhof, Xinlei Pan, Xuan Zhou
We propose using deep reinforcement learning to solve dynamic stochastic general equilibrium models.
no code implementations • 4 Dec 2019 • Alexandre Belloni, Mingli Chen, Oscar Hernan Madrid Padilla, Zixuan, Wang
We propose a generalization of the linear panel quantile regression model to accommodate both \textit{sparse} and \textit{dense} parts: sparse means while the number of covariates available is large, potentially only a much smaller number of them have a nonzero impact on each conditional quantile of the response variable; while the dense part is represent by a low-rank matrix that can be approximated by latent factors and their loadings.
no code implementations • 9 Aug 2019 • Erlei Zhang, Zi Yang, Stephen Seiler, Mingli Chen, Weiguo Lu, Xuejun Gu
These findings indicated that SATPN is promising for effective breast US lesion CAD using small datasets.
no code implementations • 1 Apr 2019 • Erlei Zhang, Stephen Seiler, Mingli Chen, Weiguo Lu, Xuejun Gu
Then, the converted BFMs are used as the input of an SDL network, which performs unsupervised stacked convolutional auto-encoder (SCAE) image reconstruction guided by lesion classification.
Medical Physics
no code implementations • 30 Dec 2017 • Timothy Rozario, Troy Long, Mingli Chen, Weiguo Lu, Steve Jiang
Organs are often labeled inconsistently at different institutions (sometimes even within the same institution) and at different time periods, which poses a problem for clinical research, especially for multi-institutional collaborative clinical research where the acquired patient data is not being used effectively.